Intelligent Decision-Making with Data Fusion and Predictive Analytics for Multi-Sensor Environments
Dror Jacoby was born in Ramat Gan, Israel, in 1992, currently a PhD Student at Tel Aviv University for Electrical Engineering. He received his B.Sc. (Magna Cum Laude) and M.Sc. degrees in Electrical Engineering from the Accelerated Master Program of Tel-Aviv University in 2022. His M.Sc. Emphasis in research was on prediction analysis using model and data-driven methods, with statistical signal processing. During his M.Sc. studies, Dror was awarded the Weinstein Prize for his excellent research and academic achievements in the field of Signal Processing. He is a member of the Cellular Environmental Monitoring (CellenMon) Lab at Tel Aviv University. More recently, Dror has contributed to the New Generation Internet (NGI) initiative and has done part of his research studies at Columbia University during his Ph.D. period.
The figure illustrates the transition to new generation datasets, showcasing the integration and application of advanced algorithms within 5G and NGI networks. This transition highlights the move towards more sophisticated, real-time data analysis and predictive modeling, enabling enhanced network performance, reliability, and sensing capabilities in response to environmental factors.
In our collaboration, we’ve harnessed proactive algorithms to enhance 5G and NGI networks, focusing on sensing and communication. Our innovative approach predicts weather impacts on network signals, using advanced deep learning techniques for superior accuracy. This work has led to develop algorithms that adaptively refine based on real-world network data, improving both environmental monitoring and communication reliability. By integrating communication networks as sensor data sources, we’ve created a novel solution for the IoT sector’s challenges, demonstrating significant advancements in both theoretical and practical realms, notably within the NYC Mesh network.
Our targets in this area associated with Innovative ISAC Applications: The dual use of communication networks for sensing and data transmission will lead to novel Integrated Sensing and Communication (ISAC) applications. These applications will exploit the unique capabilities of 5G and NGI networks for both communication and environmental monitoring.
Results from 4G Networks of ISAC applications: (i) Rainfall Prediction (ii) Proative Routing
Key results anticipated from this project, with initial insights:
NYC Mesh Dataset Integration: Successful integration with the NYC Mesh dataset has enabled access to real-time, urban environmental data, enhancing our network’s sensing and predictive capabilities.
4G Network Insights: Initial results derived from 4G networks have laid the groundwork for understanding network behavior under various environmental conditions.
Preliminary Experiments with New Data: Early experiments utilizing our newly acquired dataset have begun, promising to yield insights that surpass previous benchmarks and inform future networks (5G and NGI sensors) optimizations.
Impact of the Fellowship
The fellowship aims to significantly impact through establishing both academic and industrial connections for mutual benefits (specifically nyc-mesh), including:
Advancing Technologies: Developing cutting-edge innovations in 5G and NGI networks for improved performance and sensing.
Real-World Testing: Rigorously validating new technologies in NYC in high test-bands markets through demos and pilot projects.
Strengthening Collaboration: Enhancing US/Canada and academic partnerships to foster knowledge exchange and innovation in communication networks.